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Introduction to RNA Seq Short Course Commands
Introduction to RNA Seq Short Course Commands
Class Slides
Idev session and getting data
Setting up
ssh <username>@stampede.tacc.utexas.edu cds cp -r /corral-repl/utexas/BioITeam/short_rnaseq_course/ my_short_rnaseq_course cd my_short_rnaseq_course/
Step 1: Evaluate and manipulate raw data
Count and Fastqc
cd quality_exercise head data/Sample1_R1.fastq wc -l data/Sample1_R1.fastq grep -c '^@HWI' data/Sample1_R1.fastq module spider fastqc module load fastqc fastqc -h #DONT RUN ON HEAD NODE: fastqc data/Sample1_R1.fastq
Look at Fastqc results:
Ideal dataset: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/good_sequence_short_fastqc.html
Our dataset: http://web.corral.tacc.utexas.edu/BioITeam/rnaseq_course/fastqc_exercise/Sample1_R1_fastqc/fastqc_report.html
manipulate fastq files- quality trimming and filtering
module spider fastx module load fastx_toolkit #DONT RUN ON HEAD NODE: fastx_trimmer -i data/Sample1_R1.fastq -l 90 -Q 33 -o Sample1_R1.trimmed.fastq #DONT RUN ON HEAD NODE: fastq_quality_filter -q 20 -p 80 -i data/Sample1_R1.fastq -Q 33 -o Sample1_R1.filtered.fastq grep -c '^@HWI' results/Sample1_R1.trimmed.fastq grep -c '^@HWI' results/Sample1_R1.filtered.fastq
Step 2: Map Raw Data to Reference, Assess results
Map with BWA
cd .. cd mapping_exercise module spider bwa module load bwa/0.7.12 #DONT RUN ON HEAD NODE: bwa index -a bwtsw reference/transcripts.fasta bwa mem #DONT RUN ON HEAD NODE: bwa mem ../reference/transcripts.fasta ../data/GSM794483_C1_R1_1.fq data/GSM794483_C1_R1_2.fq > C1_R1.mem.sam
Map with Tophat
module spider hisat #DONT RUN ON HEAD NODE hisat2-build reference/genome.fa reference/genome.fa #DONT RUN ON HEAD NODE: hisat2 -x ../reference/genome.fa -1 ../data/GSM794483_C1_R1_1.fq -2 ../data/GSM794483_C1_R1_2.fq -S GSM794483_C1.sam --phred33 --novel-splicesite-outfile GSM794483_C1.junctions --rna-strandness RF --dta -t
Assess Mapping Results
module load samtools #SYNTAX: samtools view -b -S samfile > bamfile samtools sort bamfile sortedbamfile samtools index sortedbamfile #BWA RESULTS samtools flagstat bwa_mem_results_transcriptome/C1_R1.mem.bam samtools idxstats bwa_mem_results_transcriptome/C1_R1.mem.bam #How is hisat2 result different from bwa head -20 hisat_exercise/results/GSM794483_C1.sam grep -v '^@' bwa_exercise/bwa_mem_results_transcriptome/C1_R1.mem.sam|head|cut -f 6 grep -v '^@' hisat_exercise/results/GSM794483_C1.sam|head|cut -f 6 #DONT RUN ON HEAD NODE grep -v '^@' hisat_exercise/results/GSM794483_C1.sam|cut -f 6|wc -l
Step 3 and Step 4 : Quantify transcripts and ID DEGs
Look at bedtools and DESeq results
cd deg_exercise/ module swap intel gcc/4.7.1 module load bedtools bedtools bedtools multicov #DONT RUN ON HEAD NODE bedtools multicov -bams hisat_results/C1_R1.sorted.bam hisat_results/C1_R2.sorted.bam hisat_results/C1_R3.sorted.bam hisat_results/C2_R1.sorted.bam hisat_results/C2_R2.sorted.bam hisat_results/C2_R3.sorted.bam -bed ../reference/genes.formatted.gtf > gene_counts.gff #What's the difference between bedtools and htseq results? #First look at the annotation file head ../mapping_exercise/reference/genes.formatted.gtf #bedtools result head gene_counts.gff wc -l gene_counts.gff #htseq result head gene_counts.htseq.gff wc -l gene_counts.htseq.gff #DESEQ2 script in:https://wikis.utexas.edu/display/bioiteam/Testing+for+Differential+Expression #DESEQ2 result: head deseq_results/DESeq-C1-vs-C2.csv #Find the top 10 upregulated genes sed 's/,/\t/g' deseq_results/DESeq-C1-vs-C2.csv|sort -n -r -k7,7|cut -f 2,7|head #If there's an idiosyncracy with sort sed 's/,/\t/g' deseq_results/DESeq-C1-vs-C2.csvsort -n -r -k7,7|grep -v 'e-0'|cut -f 2,7|head #Find the top 10 downregulated genes sed 's/,/\t/g' deseq_results/DESeq-C1-vs-C2.csv|sort -n -k7,7|cut -f 2,7|head #If there's an idiosyncracy with sort sed 's/,/\t/g' deseq_results/DESeq-C1-vs-C2.csv|sort -n -k7,7|grep -v 'e-0'|cut -f 2,7|head #Count the DEGs sed 's/,/\t/g' deseq_results/DESeq-C1-vs-C2.csv|awk '{if ((($7>=1)||($7<=-1))&&($9<=0.05)) print}'|wc -l
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